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分享</span><i class="fas fa-chevron-down"></i></a><ul class="menus_item_child"><li><a class="site-page child" href="/myblog/Gallery/"><i class="fa-fw fas fa-images"></i><span> 照片</span></a></li><li><a class="site-page child" href="/myblog/music/"><i class="fa-fw fas fa-music"></i><span> 音乐</span></a></li><li><a class="site-page child" href="/myblog/movies/"><i class="fa-fw fas fa-video"></i><span> 视频</span></a></li></ul></div><div class="menus_item"><a class="site-page" href="/myblog/link/"><i class="fa-fw fas fa-link"></i><span> 友链</span></a></div><div class="menus_item"><a class="site-page" href="/myblog/about/"><i class="fa-fw fas fa-heart"></i><span> 关于</span></a></div></div><div id="toggle-menu"><a class="site-page" href="javascript:void(0);"><i class="fas fa-bars fa-fw"></i></a></div></div></nav></header><main class="layout" id="content-inner"><div id="post"><div id="post-info"><h1 class="post-title">mysqlCookBook03</h1><div id="post-meta"><div class="meta-firstline"><span class="post-meta-date"><i class="far fa-calendar-alt fa-fw post-meta-icon"></i><span class="post-meta-label">发表于</span><time class="post-meta-date-created" datetime="2019-11-27T08:44:01.000Z" title="发表于 2019-11-27 16:44:01">2019-11-27</time><span class="post-meta-separator">|</span><i class="fas fa-history fa-fw post-meta-icon"></i><span class="post-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2023-09-07T09:44:01.900Z" title="更新于 2023-09-07 17:44:01">2023-09-07</time></span><span class="post-meta-categories"><span class="post-meta-separator">|</span><i class="fas fa-inbox fa-fw post-meta-icon"></i><a class="post-meta-categories" href="/myblog/categories/mysql/">mysql</a></span></div><div class="meta-secondline"><span class="post-meta-separator">|</span><span class="post-meta-pv-cv" id="" data-flag-title="mysqlCookBook03"><i class="far fa-eye fa-fw post-meta-icon"></i><span class="post-meta-label">阅读量:</span><span id="busuanzi_value_page_pv"><i class="fa-solid fa-spinner fa-spin"></i></span></span></div></div></div><article class="post-content" id="article-container"><h1 id="事务"><a href="#事务" class="headerlink" title="事务"></a>事务</h1><ol>
<li><p>检查数据库支持事务的存储引擎语句</p>
<pre><code> SELECT ENGINE 
 FROM
     information_schema.`ENGINES` 
 WHERE
     support IN ( &#39;YES&#39;, &#39;DEFAULT&#39; ) 
     AND TRANSACTIONS = &#39;YES&#39;;
</code></pre>
</li>
<li><p>mysql默认是auto-commit模式的,自动开事务.挂起这模式手动开启使用START TRANSACTION (or BEGIN)语句</p>
<pre><code> CREATE TABLE t (i INT) ENGINE = InnoDB;
 START TRANSACTION;
 INSERT INTO t (i) VALUES(1);
 INSERT INTO t (i) VALUES(2);
 #ROLLBACK; #执行这个语句,事务里的修改全部失效.
 COMMIT; # 执行这个,修改会真正提交到数据库
 SELECT * FROM t;

 #还有一种方式是SET autocommit = 0;也是关闭自动提交autocommit为1就是开启自动提交模式
</code></pre>
</li>
</ol>
<h1 id="统计技术"><a href="#统计技术" class="headerlink" title="统计技术"></a>统计技术</h1><h2 id="各种测量统计函数"><a href="#各种测量统计函数" class="headerlink" title="各种测量统计函数"></a>各种测量统计函数</h2><ol>
<li>观测值的数量，它们的总和及其范围<br> SUM(score) AS sum,<br> MIN(score) AS minimum,<br> MAX(score) AS maximum,</li>
<li>集中趋势的度量，例如均值(mean)，中位数和众数<br> AVG(score) AS mean,</li>
<li>变化量度，例如标准偏差(standard deviation)和方差(variance)<br> STDDEV_SAMP(score) AS ‘std.dev.’,<br> VAR_SAMP(score) AS ‘variance’</li>
</ol>
<p>STDDEV_SAMP和VAR_SAMP用于样品测量而不是人口测量.它对于一系列n值,产生基于n-1自由度的一个结果.对于人口测量,结果是基于n自由度,使用STDDEV_POP和VAR_POP替换.<br>标准偏差可用于识别离群值，即离平均值远的特征值。例如，要选择与均值相差三个以上标准偏差的值，请执行以下操作<br>        SELECT<br>            @mean :&#x3D; AVG( score ),<br>            @std :&#x3D; STDDEV_SAMP( score )<br>        FROM<br>            testscore;<br>        SELECT<br>            score<br>        FROM<br>            testscore<br>        WHERE<br>            ABS( score - @mean ) &gt; @std * 3;</p>
<h1 id="join和子查询"><a href="#join和子查询" class="headerlink" title="join和子查询"></a>join和子查询</h1><p>一个完整的join产生的所有可能的行结合被称为<em>笛卡尔积</em>.例如,一个100行的表join个200行的表那么产生的结果包含100*200&#x3D;20000 行.因此join通常包含ON条件或USING一个比较条件去产生仅被需要的匹配项.也可用使用where条件去限制join的行.</p>
<h2 id="代码演示"><a href="#代码演示" class="headerlink" title="代码演示:"></a>代码演示:</h2><p><strong>首先创建两个表:</strong></p>
<pre><code>CREATE TABLE artist (
a_id INT UNSIGNED NOT NULL AUTO_INCREMENT,# 艺术家 ID,UNSIGNED关键字是非负数
NAME VARCHAR ( 30 ) NOT NULL,# 艺术家 name
PRIMARY KEY ( a_id ),
UNIQUE ( NAME ) 
);

CREATE TABLE painting (
a_id INT UNSIGNED NOT NULL,
p_id INT UNSIGNED NOT NULL AUTO_INCREMENT,# 油画ID
title VARCHAR ( 100 ) NOT NULL,# 画主题
state VARCHAR ( 2 ) NOT NULL,# 购买状态
price INT UNSIGNED,# 购买价格
INDEX ( a_id ),
PRIMARY KEY ( p_id ) 
);
</code></pre>
<p><strong>插入一些数据</strong></p>
<pre><code>INSERT INTO artist ( NAME )
VALUES
    ( &#39;Da Vinci&#39; ),
    ( &#39;Monet&#39; ),
    ( &#39;Van Gogh&#39; ),
    ( &#39;Renoir&#39; );

INSERT INTO painting ( a_id, title, state, price )
VALUES
    ( 1, &#39;The Last Supper&#39;, &#39;IN&#39;, 34 ),
    ( 1, &#39;Mona Lisa&#39;, &#39;MI&#39;, 87 ),
    ( 3, &#39;Starry Night&#39;, &#39;KY&#39;, 48 ),
    ( 3, &#39;The Potato Eaters&#39;, &#39;KY&#39;, 67 ),
    ( 4, &#39;Les Deux Soeurs&#39;, &#39;NE&#39;, 64 );
</code></pre>
<p><strong>展示一个简单JOIN</strong></p>
<pre><code>SELECT
* 
FROM
    artist
    INNER JOIN painting 
ORDER BY
    artist.a_id;
</code></pre>
<p>这条查询会产生笛卡尔积,产生4*5&#x3D;20行数据.</p>
<p>INNER JOIN生成的结果将一个表中的值与另一个表中的值组合在一起.前面的查询没有对行匹配进行任何限制，因此联接生成所有行组合（即笛卡尔乘积）。这个结果说明了为什么这样的连接通常没有用：它产生了很多无意义的输出。<br>这个时候使用一个条件限制多余输出.</p>
<pre><code>SELECT
* 
FROM
    artist
    INNER JOIN painting 
WHERE
    artist.a_id = painting.a_id 
ORDER BY
    artist.a_id;
</code></pre>
<p>当然也可用使用ON替换where.如果比较列的名字在两个表中是相同的,那么可用使用USING条件替换,这样的话可用不用对列名指定表名如下:</p>
<pre><code>SELECT
* 
FROM
    artist
    INNER JOIN painting
USING (a_id)
ORDER BY
    a_id
</code></pre>
<p>USING和ON还是有点不同.在返回的结果中,USING只返回每个连接列的一个实例,因此a_id只出现一列,而不是两列.</p>
<ul>
<li><p>用INNER JOIN编写的联接是内部联接。它们仅对一个表中的值与另一表中的值匹配产生结果</p>
</li>
<li><p>outer join(left join或right join或a NOT IN子连接)外连接也能产生匹配结果,但是还能展示一个表中哪些值从另一个表中丢失了.</p>
</li>
</ul>
<p><strong>left join</strong><br>左连接.意思是右表没有匹配左表的项.左表全显,右表不匹配的用null替代.</p>
<pre><code>SELECT
    * 
FROM
    artist
    RIGHT JOIN painting 
ON
    artist.a_id = painting.a_id 
ORDER BY
    artist.a_id;
</code></pre>
<p>左artist的a_id是{1,4},右表painting中缺了a_id&#x3D;2的数据.那么左边a_id&#x3D;2的数据显示.右边用null补全</p>
<p><strong>right join</strong><br>右连接,和左连接相反就是了.</p>
<p><strong>NOT IN子连接</strong></p>
<pre><code>SELECT 
    * 
FROM 
    artist 
WHERE a_id NOT IN (SELECT a_id FROM painting);
</code></pre>
<p><strong>自然连接(natural)</strong></p>
<p>在一种情况下:就是你想在出现在两个表中的每一列的基础上比较,你可以使用 <strong>NATURAL LEFT JOIN 或 NATURAL RIGHT JOIN</strong><br>并且不再需要写on或using条件了</p>
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta">文章作者: </span><span class="post-copyright-info"><a href="https://zhangbo4881820.gitee.io/myblog">brad 随风起舞</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta">文章链接: </span><span class="post-copyright-info"><a href="https://zhangbo4881820.gitee.io/myblog/posts/64374/">https://zhangbo4881820.gitee.io/myblog/posts/64374/</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta">版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://zhangbo4881820.gitee.io/myblog" target="_blank">静待花开</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"><a class="post-meta__tags" href="/myblog/tags/mysql/">mysql</a></div><div class="post_share"><div class="social-share" 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